New dimensions and new tools to realize the potential of RDoC: digital phenotyping via smartphones and connected devices.

Mobile and connected devices like smartphones and wearable sensors can facilitate the collection of novel naturalistic and longitudinal data relevant to psychiatry at both the personal and population level. The National Institute of Mental Health's Research Domain Criteria framework offers a useful roadmap to organize, guide and lead new digital phenotyping data towards research discoveries and clinical advances.

Methodology and Reporting of Mobile Heath and Smartphone Application Studies for Schizophrenia.

The increasing prevalence of mobile devices among patients of all demographic groups has the potential to transform the ways we diagnose, monitor, treat, and study mental illness. As new tools and technologies emerge, clinicians and researchers are confronted with an increasing array of options both for clinical assessment, through digital capture of the essential behavioral elements of a condition, and for intervention, through formalized treatments, coaching, and other technology-assisted means of patient communication. And yet, as with any new set of tools for the assessment or treatment of a medical condition, establishing and adhering to reporting guidelines-that is, what works and under what conditions-is an essential component of the translational research process. Here, using the recently published World Health Organization mHealth Evaluation, Reporting and Assessment guidelines for evaluating mobile health applications, we review the methodological strengths and weaknesses of existing studies on smartphones and wearables for schizophrenia. While growing evidence supports the feasibility of using mobile tools in severe mental illness, most studies to date failed to adequately report accessibility, interoperability, costs, scalability, replicability, data security, usability testing, or compliance with national guidelines or regulatory statutes. Future research efforts addressing these specific gaps in the literature will help to advance our understanding and to realize the clinical potential of these new tools of psychiatry.

Characterizing Smartphone Engagement for Schizophrenia: Results of a Naturalist Mobile Health Study.

INTRODUCTION: Despite growing interest in smartphone apps for schizophrenia, little is known about how these apps are utilized in the real world. Understanding how app users are engaging with these tools outside of the confines of traditional clinical studies offers an important information on who is most likely to use apps and what type of data they are willing to share. METHODS: The Schizophrenia and Related Disorders Alliance of America, in partnership with Self Care Catalyst, has created a smartphone app for schizophrenia that is free and publically available on both Apple iTunes and Google Android Play stores. We analyzed user engagement data from this app across its medication tracking, mood tracking, and symptom tracking features from August 16th 2015 to January 1st 2017 using the R programming language. We included all registered app users in our analysis with reported ages less than 100. RESULTS: We analyzed a total of 43,451 mood, medication and symptom entries from 622 registered users, and excluded a single patient with a reported age of 114. Seventy one percent of the 622 users tried the mood-tracking feature at least once, 49% the symptom tracking feature, and 36% the medication-tracking feature. The mean number of uses of the mood feature was two, the symptom feature 10, and the medication feature 14. However, a small subset of users were very engaged with the app and the top 10 users for each feature accounted for 35% or greater of all entries for that feature. We find that user engagement follows a power law distribution for each feature, and this fit was largely invariant when stratifying for age or gender. DISCUSSION: Engagement with this app for schizophrenia was overall low, but similar to prior naturalistic studies for mental health app use in other diseases. The low rate of engagement in naturalistic settings, compared to higher rates of use in clinical studies, suggests the importance of clinical involvement as one factor in driving engagement for mental health apps. Power law relationships suggest strongly skewed user engagement, with a small subset of users accounting for the majority of substantial engagements. There is a need for further research on app engagement in schizophrenia.

Dynamics of market correlations: taxonomy and portfolio analysis.

The time dependence of the recently introduced minimum spanning tree description of correlations between stocks, called the "asset tree" has been studied in order to reflect the financial market taxonomy. The nodes of the tree are identified with stocks and the distance between them is a unique function of the corresponding element of the correlation matrix. By using the concept of a central vertex, chosen as the most strongly connected node of the tree, an important characteristic is defined by the mean occupation layer. During crashes, due to the strong global correlation in the market, the tree shrinks topologically, and this is shown by a low value of the mean occupation layer. The tree seems to have a scale-free structure where the scaling exponent of the degree distribution is different for "business as usual" and "crash" periods. The basic structure of the tree topology is very robust with respect to time. We also point out that the diversification aspect of portfolio optimization results in the fact that the assets of the classic Markowitz portfolio are always located on the outer leaves of the tree. Technical aspects such as the window size dependence of the investigated quantities are also discussed.

Structure and tie strengths in mobile communication networks.

Electronic databases, from phone to e-mails logs, currently provide detailed records of human communication patterns, offering novel avenues to map and explore the structure of social and communication networks. Here we examine the communication patterns of millions of mobile phone users, allowing us to simultaneously study the local and the global structure of a society-wide communication network. We observe a coupling between interaction strengths and the network's local structure, with the counterintuitive consequence that social networks are robust to the removal of the strong ties but fall apart after a phase transition if the weak ties are removed. We show that this coupling significantly slows the diffusion process, resulting in dynamic trapping of information in communities and find that, when it comes to information diffusion, weak and strong ties are both simultaneously ineffective.